Evaluating Large Language Models on Medical Evidence Summarization is a research paper published in medRxiv (2023). On theSindex it has a DataRank of 0. It has been cited 40 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph β no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full β never from an abstract alone.
National Science Foundation
Grant: 2303038
Collaborative Research: NSF-CSIRO: RESILIENCE: Graph Representation Learning for Fair Teaming in Crisis Response
National Institutes of Health
Grant: 5R00LM013001-04
A framework to enhance radiology structured report by invoking NLP and DL: Models and Applications
National Institutes of Health
Grant: 5R01LM009886-02
Bridging the Semantic Gap Between Research Eligibility Criteria and Clinical Data
National Science Foundation
Grant: 2019844
AI Institute: Institute for Foundations of Machine Learning
National Institutes of Health
Grant: 3P30CA013696-21S1
CANCER CENTER CORE SUPPORT GRANT
National Institutes of Health
Grant: 1R01LM014306-01
Closing the loop with an automatic referral population and summarization system
National Science Foundation
Grant: 2145640
CAREER: Knowledge-enhanced and interpretable radiology report generation
NLM NIH HHS
Grant: R00 LM013001
NLM NIH HHS
Grant: R01 LM009886
Fields of Study
Keywords
Sustainable Development Goals